adaptive_splines_params: Tuning Parameters for Adaptive Splines Surface Models

In bayesmodels: The 'Tidymodels' Extension for Bayesian Models

Description

Tuning Parameters for Adaptive Splines Surface Models

Usage

splines_degree(range = c(0L, 5L), trans = NULL)

max_degree(range = c(0L, 5L), trans = NULL)

max_categorical_degree(range = c(0L, 5L), trans = NULL)

min_basis_points(range = c(0L, 1000L), trans = NULL)

Arguments

range	A two-element vector holding the defaults for the smallest and largest possible values, respectively.
trans	A trans object from the scales package, such as scales::log10_trans() or scales::reciprocal_trans(). If not provided, the default is used which matches the units used in range. If no transformation, NULL.

Details

The main parameters for Adaptive Splines Surface models are:

• splines_degree: degree of splines. Stability should be examined for anything other than 1.

• max_degree: integer for maximum degree of interaction in spline basis functions.

• max_categorical_degree: (categorical input only) integer for maximum degree of interaction of categorical inputs.

• min_basis_points: minimum number of non-zero points in a basis function

Value

A parameter

A parameter

A parameter

A parameter

Examples

splines_degree()

max_degree()

min_basis_points()

bayesmodels documentation built on June 29, 2021, 1:06 a.m.